Bringg
AnalyticsEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Analytics Engineer at Bringg. Skills: SQL, Python, dbt, BigQuery. Leverage Medallion Pipeline. Optimize dbt data models”
What You'll Achieve.
Maximize potential of data ecosystem; Drive future data growth; Support strategic initiatives; Maintain robust data models; Ensure single source of truth; Fuel advanced analytics; Fuel machine learning projects; Fuel GenAI operations
What They're Looking For.
Must Have
4+ years of experience in data analytics, BI development, or data engineering, proficiency in SQL, proven track record building or maintaining data pipelines, Solid engineering fundamentals, Solid grasp of engineering best practices
Nice to Have
Familiarity with NoSQL or operational databases, Experience with BI ecosystem integration, Exposure to MLOps, AI/ML pipelines, or GenAI tooling, Experience with Infrastructure as Code
What You'll Do.
Leverage Medallion Pipeline
Optimize dbt data models
Extend dbt data models
Enforce dbt data tests
Define model health scores
Maintain column-level documentation
Scale unified dbt Semantic Layer
Bridge engineering and impact
Ingest new data sources
Promote best practices
Write performance-tuned SQL
How You'll Work.
Team & Collaboration
Collaborate with Data Engineers; Collaborate with Data Scientists; Collaborate with BizOps teams
Full Job Description
Bringg is the infrastructure behind delivery operations for some of the world's largest retailers. Every year, we process over 200 million orders through our smart, automated omnichannel platform experience. When it works, deliveries land on time. When it doesn't, customers feel it fast - and so do we. We are looking for an Analytics Engineer to maximize the potential of our data ecosystem and drive its future growth. On a day-to-day basis, you will leverage our fully established Medallion Data Architecture in Google BigQuery, using SQL, Python, and dbt to implement new data solutions, support upcoming strategic initiatives, and maintain robust data models. By managing our unified semantic layer and treating data as code, you will ensure a single source of truth that directly fuels Bringg's advanced analytics, machine learning projects, and GenAI operations. In this role, you will: Leverage & Scale the Medallion Pipeline: Own, optimize, and extend our production-ready dbt data models across Bronze, Silver, and Gold layers in Google BigQuery to support new business use cases. Ensure Data Quality & Governance: Implement and enforce robust dbt data tests to surface inconsistencies early, define model health scores, and maintain comprehensive column-level documentation. Own the Semantic Layer: Maintain and scale our unified dbt Semantic Layer, guaranteeing a single source of truth for business metrics utilized by internal business operations, customer-facing embedded analytics, and AI/ML initiatives. Bridge Engineering and Impact: Collaborate closely with Data Engineers, Data Scientists, and BizOps teams to ingest new data sources (via platforms like Estuary) and transform them into analytical readiness. Promote Best Practices: Write clean, modular, and performance-tuned SQL, treating data pipelines with a software engineering mindset (version control, code reviews, and automated deployment). What you Bringg 4+ years of experience in data analytics, BI development, or d
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